DESIGNING ONLINE COURSES TO PROMOTE STUDENT RETENTION

J. EDUCATIONAL TECHNOLOGY SYSTEMS, Vol. 36(1) 105-112, 2007-2008 DESIGNING ONLINE COURSES TO PROMOTE STUDENT RETENTION BETH DIETZ-UHLER AMY FISHER ANDREA HAN Miami University, Middletown, Ohio ABSTRACT Although the issue of student retention is a campus-wide one, it is of special interest in online distance learning courses, where retention rates are reported to be lower than in face-to-face classes. Among the explanations and theories of retention rates in online courses, one that struck us as most useful is a structural one, namely, course design. The question we raise is, can online course designs promote student retention? In this article, we report on how we used Quality Matters to design and revise online courses in psychology and statistics. Quality Matters, a research-based initiative, advocates the use of eight general review standards to review online courses. In our psychology and statistics courses, our retention rate across multiple offerings of both courses is approximately 95%. In higher education, the issue of student retention is gaining importance as colleges and universities continue to struggle to retain students [1, 2]. In online distance learning, student retention is apparently an even more important issue, as retention rates are reported to be lower in online than face-to-face courses. For example, Carr [3] reported that retention rates in online distance learning courses ranged from 50% to 80%, while the rates for face-to-face courses typically range 2007, Baywood Publishing Co., Inc. doi: 10.2190/ET.36.1.g http://baywood.com 105

106 / DIETZ-UHLER, FISHER AND HAN from 80%-90%. Prendergrast [4] reports that retention rates in online courses range from 25% to 75%. Although the majority of the reported data on retention rates is anecdotal, and there may be issues related to defining and measuring rates of retention in online and face-to-face courses, it is an issue that clearly deserves attention. In this article, we briefly review definitions of student retention, explanations for dropping online courses, and models of student retention. We then report on how we used Quality Matters to design and revise an introductory psychology course and a statistics course, as well as how those course designs contribute to a successful retention rate across multiple semesters. DEFINING AND MEASURING STUDENT RETENTION The wide range of retention rates reported for online distance learning courses might be attributable to how retention is defined and measured [2]. Definitions of retention range from fairly liberal (percentage of students who do not withdraw from or who pass a course, percentage of students with a grade of C or better) to fairly conservative (percentage of students who started the first module or assignment and remained in the course until the end, percentage of students whose names appeared on the roster at the beginning of the course and at the end of the course). While the importance of adopting a common definition of retention cannot be overstated, it is beyond the scope of this article to make a case for adoption of any of the definitions stated in reports of retention rates. For our purposes, we define and measure retention as the number of students who start the course (i.e., complete or attempt to complete the first module) and remain in the course until its completion. EXPLANATIONS FOR DROPPING OUT There exists a fair amount of anecdotal evidence indicating why students drop online courses. For example, Carr [3] interviewed online course instructors around the country and found such reasons for dropping online courses as having family and work obligations, marriages, job changes, and personal transitions. Others [4] point to course design issues and suggest that courses that are not stimulating or worth student s time or effort will lead to a higher drop-out rate. More systematic investigations suggest that not feeling connected to other students in the course contributed to a high drop-out rate in online courses [5]. A study using both archival and survey data shows that reasons such as carrying a large course-load, limited experience in higher education, less experience in online courses, and leading busy lives outside of school contributes to the drop-out rate [6]. Clearly, reasons for dropping out of online courses vary a great deal and include a variety of issues such personal, academic, and structural issues. Such variability

DESIGNING ONLINE COURSES / 107 poses challenges when contemplating how to address the retention problem. As such, models of retention in online courses can be quite cumbersome. MODELS OF STUDENT RETENTION The literature on retention in online courses is littered with advice, largely anecdotal, on how to improve the rates of retention. For example, Miller [7] provides a list of critical guidelines (e.g., provide prompt feedback to assignments and responses to queries ) and guidelines to develop over time (e.g., help the student to make institutional identification and connection ) to improve student retention. Prendergrast [4] discusses a variety of course design, pre-course student briefing, and online tutoring issues to improve retention rate. O Brien and Renner [8] report on several factors that have improved the retention rate in their online courses, including improving the comfort level of students with technology, creating trust in online instructors, and encouraging highly interactive experiences. A comprehensive model of retention in online courses was recently designed by Berge and Huang [9]. It is based on numerous models of retention in traditional courses. The model focuses on three clusters of variables, including personal, institutional, and circumstantial variables. Personal variables include demographics, individual variables (e.g., academic skills, motivation), and prior educational experiences. Institutional variables include bureaucratic (e.g., mission and policy), academic (e.g., structural system), and social variables (e.g., mechanisms for social integration). Finally, circumstantial variables include institutional variables (e.g., academic interactions) and interaction external to the institution (e.g., life circumstances, work circumstances). When contemplating how to improve the retention rate in online courses, there is clearly a plethora of issues to consider and strategies to pursue. It is potentially unproductive to try to consider all of the issues and strategies, so we focused on one strategy, namely, the design of the course. Although on the surface, this seems a simple and straightforward strategy, it is in fact fairly complicated. To aid us in designing online courses that would improve rates of retention, we used the Quality Matters standards. QUALITY MATTERS Quality Matters is a toolset by which online courses are reviewed for quality, defined as key elements shown by research to improve student success. Courses are reviewed on the basis of national standards of best practice and research on instructional design. The primary goals of Quality Matters are to promote student learning and to guide continual quality improvement of online courses. The review process is a faculty-driven, collegial peer review. In order to meet the Quality Matters expectations, courses are reviewed on eight general review

108 / DIETZ-UHLER, FISHER AND HAN standards: course overview and introduction, learning objectives, assessment and measurement, resources and materials, learner interaction, course technology, learner support, and accessibility. There are a total of 40 specific review standards distributed across the eight general review standards. These standards are based on research and all shown to positively affect student learning. Two courses, introduction to psychology and statistics, underwent a Quality Matters review with the goal of improving the courses so that student learning improved and the student retention rate increased. Below we describe the components of these two online courses that adhere to the elements for each of the national standards. Course Overview and Introduction This general standard focuses on the overall design of the course, navigational information, course information, and information about the instructor and student. In both the introduction to psychology and the statistics courses, the elements of this standard are met by including detailed information in the course syllabus about how to complete assignments, how grades are established, expectations for the instructor and student communications, and expectations for the course (e.g., http://www.users.muohio.edu/uhlerbd/psy111/psy111info.html). Additionally, in the introduction to psychology course, all students are required to complete an Introduction to Online Learning module which includes information about setting up e-mail, basic computer skills required by the university, an assessment to determine if the student is ready for online learning, and an assessment of the student s learning style (http://www.users.muohio.edu/uhlerbd/psy111/psy111moda.html). Learning Objectives and Competencies The elements in this general review standard include clearly defined and measurable learning objectives at both the course and unit/module level that address content mastery, critical thinking skills, and core learning skills, instructions on how students can meet the learning objectives, and having learning objectives which are measurable. In both the introduction to psychology and statistics courses, each module clearly states the learning objectives for the module. For both courses, each of the modules contain a variety of learning activities for students to engage in to meet the learning objectives (e.g., http://www.users.muohio.edu/uhlerbd/psy111/psy111modthree.html). Assessment and Measurement The elements in this standard include assessment strategies to measure learning and document student progress in meeting the learning objectives. In the introduction to psychology course, students are given ample opportunity to self-check

DESIGNING ONLINE COURSES / 109 their level of understanding for each of the learning objectives. Students can engage in a variety of activities, including reviewing lecture notes, watching a video, completing an interactive crossword puzzle, engaging in simulations, and reviewing Web sites. For each activity that students engage in (they are required to complete three activities), they are required to reflect on their learning by answering four questions and submitting their answers on a Web-based form to the instructor (http://www.users.muohio.edu/uhlerbd/activity_form.htm). The four questions include: Identify one important concept, research finding, theory, or idea in psychology that you learned while completing this activity? Why do you believe that this concept, research finding, theory, or idea in psychology is important? Apply what you have learned from this activity to some aspect of your life. What question(s) has the activity raised for you? What are you still wondering about? Students receive detailed feedback (via e-mail) from the instructor for each of the activities. Similarly, in the statistics course, students are required to complete homework assignments designed to assess whether they have achieved the learning objectives for the module. To accommodate students with varying technologies, the instructor allows for multiple submission strategies. Some students use e-mail attachments, some fax their work, and others manually submit written work. The e-mail attachments also come in a variety of manners; one student resorted to digital photographs. The instructor provides them with detailed feedback about their homework (via e-mail). Using a tablet PC, the instructor is able to grade the homework in a traditional manner with typical comments and send the students feedback fairly easily and quickly. Homework keys with extended explanations are available to supplement the graded work. Assignments are due weekly, even during weeks that students are tested so that students remain continually engaged and concerned about the course. Resources and Materials The elements in this general review standard focus primarily on the inclusion of instructional materials that are comprehensive enough to achieve the stated learning objectives. In the introduction to psychology course, each module contains publisher-developed activities for students to engage in to meet the learning objectives. For the statistics course, each module includes instructorprepared lectures created with Microsoft Producer. Each lecture integrates a PowerPoint-like presentation with audio and video of the instructor. In addition, some modules include screen capture to illustrate how to use software and video tutorials on how to program graphing calculators. The instructor also includes additional informational files for students which are designed to supplement the

110 / DIETZ-UHLER, FISHER AND HAN textbook. Finally, the instructor answers students questions about the material in one of two ways; either by making reference to a frequently asked questions portion of the course, or by using the program Lecture Scribe (available free at http://www.cs.clemson.edu/~bcdean/lscribe/) a flash-based screen capture of anything written on a tablet PC screen. This allows the instructor to easily demonstrate the steps involved in solving mathematical equations. Learner Interaction The elements of this general review standard include meaningful instructorstudent and student-student interaction. In the introduction to psychology course, students interact with the instructor on e-mail and in the discussion board about the course material for each module. Students interact with each other on the discussion board via three forums. One is devoted to open discussion and is designed to mimic the types of informal conversations students would likely have if they met face-to-face. Another is related to the course material. The third is through group-led discussions in which a group of students leads a discussion about the course material for one module. In the statistics course, students have frequent interaction with the instructor via e-mail and with Lecture Scribe, where they can observe how their instructor solves a statistics problem in nearly real time. In the spirit of continual improvement, the instructor in the statistics course is developing discussion board activities to engage the students in more student-to-student interaction. Course Technology The goal of this general review standard is to assure that online courses include technology that enhances student learning and fosters learner interactivity. Both the introduction to psychology and statistics courses make use of a sophisticated learning management system (Blackboard), including the use of the discussion board, gradebook, e-mail, and the administration of online exams. Additionally, the course syllabus provides information to students about the technologies used for the course, including detailed information about how to download and install any required software or plug-ins. In the statistics course, students receive information about the technology resources available to them through the university, information about how to download required software, and video tutorials demonstrating how to use a graphing calculator. Learner Support The elements of this general review standard include providing a clear description of the technical, academic, and student support services offered to students. In both the introduction to psychology and statistics courses, students are provided with information about how to obtain technical assistance from the

campus computer center. Students are also provided with contact information and location for the campus student services center. Accessibility DESIGNING ONLINE COURSES / 111 The goal of this standard is to evaluate whether an online course is accessible to all students. In both the introduction to psychology and statistics courses, detailed information about disabilities and the university s disabilities services center is provided to students. The activities for the psychology course are designed to be accessible for students with visual or hearing impairments. Material is presented in a variety of ways and can be adapted for students with specific disabilities. In addition, Blackboard is ADA compatible. CONCLUSION By providing our students with high-quality courses that meet the Quality Matters standards, we maintain that our students are receiving quality instruction that fosters learning. In addition, it is likely because the expectations and policies of our courses are clearly stated, and because students are provided with rich, interactive, and engaging learning experiences, that our retention rates are higher than the averages reported for online courses. In the introduction to psychology course, the average retention rate over 11 course offerings is 95.5%. In the statistics course, the average retention rate over six semesters is 95%. On the basis of our experiences with Quality Matters, we highly recommend its use in designing and revising online courses. While we acknowledge that our experiences are largely anecdotal, and that scientific evidence is needed to test whether courses created with a Quality-Matters review have better retention rates than courses not designed with such a review, we maintain that this article can serve as an important starting point for a dialogue about how course designs can improve retention rates in online courses. With the attention the high attrition rate of online courses is receiving, efforts such as this to design a course with quality in mind go far to help resolve this problem. REFERENCES 1. J. V. Boettcher, The State of Distance Education in the U.S.: Surprising Realities, Syllabus Magazine, pp. 36-40, March 2000. 2. R. Levitz, L. Noel, and B. J. Richter, Strategic Moves for Retention Success, in Promising Practices in Recruitment, Remediation, and Retention, G. H. Gaither (ed.), pp. 31-49, Winter 1999. 3. S. Carr, As Distance Education Comes of Age, the Challenge is Keeping the Students, Chronicle of Higher Education, p. A39, February 11, 2000, retrieved March 15, 2007, from http://chronicle.com/weekly/v46/i23/23a00101.htm

112 / DIETZ-UHLER, FISHER AND HAN 4. G. A. Prendergrast, Keeping Online Student Dropout Numbers Low, GlobalEducator.com, 2003, retrieved March 15, 2007, from http://www.whirligig.com.au/globaleducator/articles/gerardprendergrast2003.pdf 5. D. Link and S. Scholtz, Educational Technology and the Faculty Role: What You Don t Know Can Hurt You, Nurse, 25(6), pp. 274-276, 2000. 6. K. Moore, J. Bartkovich, M. Fetzner, and S. Ison, Success in Cyberspace: Student Retention in Online Courses, Journal of Applied Research in the Community College, 10(2), pp. 107-118, 2003. 7. S. K. Miller, Online, Distance Learning Instructor Guidelines to Improve Student Retention, Maricopa Learning Exchange, retrieved March 15, 2007 from http://www.mcli.dist.maricopa.edu/mlx/slip.php?item=1372 8. B. S. O Brien and A. L. Renner, Online Student Retention: Can It Be Done?, Association for the Advancement of Computing in Education, 2002, retrieved March 15, 2007 from http://eric.ed.gov/ericdocs/data/ericdocs2/content_storage_01/0000000b/80/21/fc/ 90.pdf 9. Z. L. Berge and Y. Huang, A Model for Sustainable Student Retention: A Holistic Perspective on the Student Dropout Problem with Special Attention to e-learning, DEOSNEWS, 13(5), 2004, retrieved March 15, 2007 from http://www.ed.psu.edu/acsde/deos/deosnews/deosnews13_5.pdf Direct reprint requests to: Beta Dietz-Uhler Department of Psychology Miami University Middletown, OH 45042 e-mail: uhlerbd@muohio.edu